Wavelet-Trend ML Integration [Alpha Extract]

21 de jun.

Alpha-Extract Volatility Quality Indicator

The Alpha-Extract Volatility Quality (AVQ) Indicator provides traders with deep insights into market volatility by measuring the directional strength of price movements. This sophisticated momentum-based tool helps identify overbought and oversold conditions, offering actionable buy and sell signals based on volatility trends and standard deviation bands.

🔶 CALCULATION

The indicator processes volatility quality data through a series of analytical steps:

• Bar Range Calculation: Measures true range (TR) to capture price volatility.
  
• Directional Weighting: Applies directional bias (positive for bullish candles, negative for bearish) to the true range.
  
• VQI Computation: Uses an exponential moving average (EMA) of weighted volatility to derive the Volatility Quality Index (VQI).
  
• Smoothing: Applies an additional EMA to smooth the VQI for clearer signals.
  
• Normalization: Optionally normalizes VQI to a -100/+100 scale based on historical highs and lows.
  
• Standard Deviation Bands: Calculates three upper and lower bands using standard deviation multipliers for volatility thresholds.
  
• Signal Generation: Produces overbought/oversold signals when VQI reaches extreme levels (±200 in normalized mode).
  

Formula:

• Bar Range = True Range (TR)
  
• Weighted Volatility = Bar Range × (Close > Open ? 1 : Close < Open ? -1 : 0)
  
• VQI Raw = EMA(Weighted Volatility, VQI Length)
  
• VQI Smoothed = EMA(VQI Raw, Smoothing Length)
  
• VQI Normalized = ((VQI Smoothed - Lowest VQI) / (Highest VQI - Lowest VQI) - 0.5) × 200
  
• Upper Band N = VQI Smoothed + (StdDev(VQI Smoothed, VQI Length) × Multiplier N)
  
• Lower Band N = VQI Smoothed - (StdDev(VQI Smoothed, VQI Length) × Multiplier N)
  

🔶 DETAILS

Visual Features:

• VQI Plot: Displays VQI as a line or histogram (lime for positive, red for negative).
  
• Standard Deviation Bands: Plots three upper and lower bands (teal for upper, grayscale for lower) to indicate volatility thresholds.
  
• Reference Levels: Horizontal lines at 0 (neutral), +100, and -100 (in normalized mode) for context.
  
• Zone Highlighting: Overbought (⋎ above bars) and oversold (⋏ below bars) signals for extreme VQI levels (±200 in normalized mode).
  
• Candle Coloring: Optional candle overlay colored by VQI direction (lime for positive, red for negative).
  
• Interpretation:
  
• VQI ≥ 200 (Normalized): Overbought condition, strong sell signal.
  
• VQI 100–200: High volatility, potential selling opportunity.
  
• VQI 0–100: Neutral bullish momentum.
  
• VQI 0 to -100: Neutral bearish momentum.
  
• VQI -100 to -200: High volatility, strong bearish momentum.
  
• VQI ≤ -200 (Normalized): Oversold condition, strong buy signal.
  

🔶 EXAMPLES

• Overbought Signal Detection: When VQI exceeds 200 (normalized), the indicator flags potential market tops with a red ⋎ symbol.
  
• Example: During strong uptrends, VQI reaching 200 has historically preceded corrections, allowing traders to secure profits.
  
• Oversold Signal Detection: When VQI falls below -200 (normalized), a lime ⋏ symbol highlights potential buying opportunities.
  
• Example: In bearish markets, VQI dropping below -200 has marked reversal points for profitable long entries.
  
• Volatility Trend Tracking: The VQI plot and bands help traders visualize shifts in market momentum.
  
• Example: A rising VQI crossing above zero with widening bands indicates strengthening bullish momentum, guiding traders to hold or enter long positions.
  
• Dynamic Support/Resistance: Standard deviation bands act as dynamic volatility thresholds during price movements.
  
• Example: Price reversals often occur near the third standard deviation bands, providing reliable entry/exit points during volatile periods.
  

🔶 SETTINGS

Customization Options:

• VQI Length: Adjust the EMA period for VQI calculation (default: 14, range: 1–50).
  
• Smoothing Length: Set the EMA period for smoothing (default: 5, range: 1–50).
  
• Standard Deviation Multipliers: Customize multipliers for bands (defaults: 1.0, 2.0, 3.0).
  
• Normalization: Toggle normalization to -100/+100 scale and adjust lookback period (default: 200, min: 50).
  
• Display Style: Switch between line or histogram plot for VQI.
  
• Candle Overlay: Enable/disable VQI-colored candles (lime for positive, red for negative).
  

The Alpha-Extract Volatility Quality Indicator empowers traders with a robust tool to navigate market volatility. By combining directional price range analysis with smoothed volatility metrics, it identifies overbought and oversold conditions, offering clear buy and sell signals. The customizable standard deviation bands and optional normalization provide precise context for market conditions, enabling traders to make informed decisions across various market cycles.

Notas de Lançamento

The Wavelet-Trend ML Integration indicator combines advanced wavelet decomposition with an adaptive neural network to create a sophisticated trend analysis tool. This hybrid approach uses multi-scale wavelet analysis for noise reduction and trend detection while employing machine learning algorithms that continuously adapt to changing market conditions, providing traders with highly refined buy and sell signals.

🔶 CALCULATION

• Wavelet Processing: Performs multi-scale wavelet decomposition using short and long scale lengths to extract trend components from price data
  
• Neural Network Engine: Implements adaptive neural network with 6 market features (momentum, volatility, trend strength, oscillation, velocity, resistance detection)
  
• Feature Engineering: Analyzes RSI momentum, CCI volatility, DMI trend strength, custom oscillation detectors, price velocity, and dynamic resistance levels
  
• Adaptive Learning: Neural network continuously adjusts weights based on prediction errors using backpropagation
  
• Signal Fusion: Intelligently combines wavelet and AI predictions into normalized signal ranging from -2 to +2
  

🔶 DETAILS

• 
  Visual Features:
  
  
• Signal Candles: Color-coded candlesticks reflecting signal direction (green for bullish, red for bearish)
  
• Reference Zones: Horizontal lines marking signal strength levels (-1 to +1 with intermediate zones)
  
• Gradient Fill: Dynamic background coloring between signal line and zero line
  
• Signal Arrows: Clear buy/sell indicators on signal crossovers
  
• Dual Plot System: Main signal line with zero-line reference for trend clarity
  
• Interpretation:
  
• Above +0.75: Strong bullish momentum - consider long positions
  
• +0.25 to +0.75: Moderate bullish trend - bullish bias
  
• -0.25 to +0.25: Neutral zone - sideways movement likely
  
• -0.75 to -0.25: Moderate bearish trend - bearish bias
  
• Below -0.75: Strong bearish momentum - consider short positions
  
• Zero Line Crosses: Primary buy (crossing above) and sell (crossing below) signals
  
• Extreme Levels (±1.0+): Potential reversal zones - exercise caution
  

🔶 EXAMPLES

• Trend Confirmation: The wavelet component filters market noise while the AI engine confirms trend direction through multiple market features. Example: When both wavelet analysis shows upward momentum and AI prediction indicates bullish features alignment, the combined signal provides high-confidence long entry.
  
• Adaptive Market Response: Neural network learns from recent market behavior, adjusting sensitivity to current volatility and trend characteristics. Example: During high volatility periods, the AI reduces sensitivity to prevent false signals, while in trending markets it increases responsiveness to capture momentum.
  
• Multi-Timeframe Analysis: Wavelet decomposition captures both short-term price movements and longer-term trend components simultaneously. Example: Short-scale wavelet detects immediate price action while long-scale component ensures alignment with broader trend direction.
  
• Signal Quality Enhancement: The fusion of technical analysis (wavelets) with machine learning creates more reliable signals than either method alone. Example: Traditional crossover signals are enhanced by AI confirmation, reducing whipsaws in choppy markets while maintaining sensitivity in trending conditions.
  

🔶 SETTINGS

• 
  Wavelet Configuration:
  
  
• Short/Long Scale Lengths (default 12/23): Controls sensitivity to different trend timeframes
  
• Signal Smoothing (default 8): Reduces noise in final output
  
• Normalization Lookback (default 1000): Historical period for signal scaling
  
• Noise Reduction: Optional smoothing for cleaner signals
  
  AI Neural Network:
  
  
• Adaptation Rate (default 0.08): Learning speed of neural network
  
• Feature Periods: Customizable lengths for momentum, volatility, trend, oscillation, velocity, and resistance detection
  
• Neural Weights: Balanced weighting system for optimal feature integration
  
  Display Options:
  
• Color Customization: Bullish/bearish signal colors
  
• Reference Lines: Toggle horizontal level guides
  
• Alert System: Configurable notifications for signal changes
  

The Wavelet-Trend ML Integration indicator represents a cutting-edge approach to technical analysis, combining the mathematical precision of wavelet decomposition with the adaptive intelligence of machine learning. This sophisticated tool helps traders identify high-probability opportunities while filtering out market noise through its dual-analysis framework.